An Exploratory Study of Dynamic Capabilities and Performance Improvement in Hospitals.

GOAL: Recent efforts to push hospitals to provide high-value care have relied on payment incentives. However, evidence indicates that 70% to 90% of performance improvement projects do not achieve their desired goals. Therefore, in addition to managing external industry pressures, hospitals need to develop performance improvement (PI) capabilities that enable them to capitalize on improvement opportunities, effectively develop and adopt solutions, and ensure the sustainability of improvements over time. While operational capabilities enable hospitals to produce and deliver services, more is needed to attain and sustain superior performance. Dynamic capabilities drive changes in operational capabilities to meet environmental demands. Dynamic capabilities also enable hospitals to renew and reconfigure their resources to optimize performance. This paper proposes the dynamic-capabilities framework as an appropriate way to develop and manage PI capabilities in hospitals, and it discusses the implications of shifting to a strategy that is driven by dynamic-capabilities PI. METHODS: The research team designed a semi-structured interview based on a review of the literature to understand whether hospitals were engaging in the activities outlined in the dynamic-capabilities framework. Nine study participants were recruited from a convenience sample of hospital PI staff at hospitals in Massachusetts and New Hampshire. De-identified transcripts were entered into NVivo12 qualitative data analysis software, and data were thematically indexed and coded following the principles of content analysis. PRINCIPAL FINDINGS: PI structures, improvement methodologies, and weaknesses did not vary significantly among hospitals. Most hospitals had a PI department and were more likely to adopt PI projects initiated by top management. While PI staff were trained in improvement methodologies, no programs were in place that required the rest of the hospital staff to become familiar with PI methods. Common areas of weakness were PI project selection, communication, coordination, learning from current and former PI projects, and systematic approaches to sustain improvements. PRACTICAL APPLICATIONS: Dynamic PI capabilities provide an opportunity to systematically identify improvement opportunities, seize on and learn from those opportunities, and renew and reconfigure resources to optimize performance. Ad hoc PI projects are insufficient to enable a hospital to sustain superior performance. Internal and external pressures to deliver high-value patient care and services require hospitals to exceed their current PI efforts. By developing dynamic PI capabilities, hospitals will adopt a more systematic and effective approach to PI, which will likely result in superior performance.

Early Financial Impact of the COVID-19 Pandemic on U.S. Hospitals.

GOAL: The COVID-19 pandemic has left a significant impact on hospitals' operations, expenses, and revenues. However, little is known about the pandemic's financial impact on rural and urban hospitals. Our main objective was to analyze how hospital profitability changed during the first year of the pandemic. We specifically studied the association between COVID-19 infections and hospitalizations and county-level variables with operating margins (OMs) and total margins (TMs). METHODS: We obtained data from Medicare Cost Reports, the American Hospital Association Annual Survey Database, and the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) for 2012-2020. Our final dataset consisted of an unbalanced panel with 17,510 observations for urban hospitals and 17,876 observations for rural hospitals. We estimated separate hospital fixed-effects models for urban and rural hospitals' OMs and TMs. The fixed-effects models controlled for time-invariant differences across hospitals. PRINCIPAL FINDINGS: In our review of the early impact of the COVID-19 pandemic on rural and urban hospitals' profits as well as trends in OMs and TMs from 2012 to 2020, we found that OMs were inversely related to the duration of hospitals' exposure to infections in urban and rural locations. In contrast, TMs and hospitals' exposures had a positive relationship. Government relief funds, a source of nonoperating revenue, apparently allowed most hospitals to avoid financial distress from the pandemic. We also found a positive relationship between the magnitude of weekly adult hospitalizations and OMs in urban and rural hospitals. Size, participation in group purchasing organizations (GPOs), and occupancy rates were positively related to OMs, with size and participation in GPOs relating to scale economies and occupancy rates reflecting capital efficiencies. PRACTICAL APPLICATIONS: Hospitals' OMs have been declining since 2014. The pandemic made this decline worse, especially for rural hospitals. Federal relief funds, along with investment income, helped hospitals remain financially solvent during the pandemic. However, investment income and temporary federal aid are insufficient to sustain financial well-being. Executives need to explore cost-saving opportunities such as joining a GPO. Small rural hospitals with low occupancy and low community COVID-19 hospitalization rates have been particularly vulnerable to the financial impact of the pandemic. Although federal relief funds have limited hospital financial distress induced by the pandemic, we maintain that the funds should have been more effectively targeted, as the mean TM increased to its highest level in a decade. The disparate results of our analysis of OMs and TMs illustrate the utility of using multiple measures of profitability.

Were hospitals with sustained high performance more successful at reducing mortality during the pandemic's second wave?

BACKGROUND: In 2019, the COVID-19 pandemic emerged. Variation in COVID-19 patient outcomes between hospitals was later reported. PURPOSE: This study aims to determine whether sustainers-hospitals with sustained high performance on Hospital Value-Based Purchasing Total Performance Score (HVBP-TPS)-more effectively responded to the pandemic and therefore had better patient outcomes. METHODOLOGY: We calculated hospital-specific risk-standardized event rates using deidentified patient-level data from the UnitedHealth Group Clinical Discovery Database. HVBP-TPS from 2016 to 2019 were obtained from Centers for Medicare & Medicaid Services. Hospital characteristics were obtained from the American Hospital Association Annual Survey Database (2019), and county-level predictors were obtained from the Area Health Resource File. We use a repeated-measures regression model assuming an AR(1) type correlation structure to test whether sustainers had lower mortality rates than nonsustainers during the first wave (spring 2020) and the second wave (October to December 2020) of the pandemic. RESULTS: Sustainers did not have significantly lower COVID-19 mortality rates during the first wave of the pandemic, but they had lower COVID-19 mortality rates during the second wave compared to nonsustainers. Larger hospitals, teaching hospitals, and hospitals with higher occupancy rates had higher mortality rates. CONCLUSION: During the first wave of the pandemic, mortality rates did not differ between sustainers and nonsustainers. However, sustainers had lower mortality rates than nonsustainers in the second wave, most likely because of their knowledge management capabilities and existing structures and resources that enable them to develop new processes and routines to care for patients in times of crisis. Therefore, a consistently high level of performance over the years on HVBP-TPS is associated with high levels of performance on COVID-19 patient outcomes. PRACTICE IMPLICATIONS: Investing in identifying the knowledge, processes, and resources that foster the dynamic capabilities needed to achieve superior performance in HVBP might enable hospitals to utilize these capabilities to adapt more effectively to future changes and uncertainty.

Sustainers: Hospitals with sustained superior performance.

PURPOSE: The purpose of this article was to investigate the organizational and market-level variables associated with sustained superior hospital performance on Value-Based Purchasing total performance scores (TPS). METHODOLOGY: TPS for 2014 through 2017 was obtained from the Centers for Medicare & Medicaid Services Hospital Compare website. Market-level data were from the 2017 Area Health Resource File, and hospital-level data were from the 2014 American Hospital Association Annual Survey database. We specified a logistic regression model to identify significant predictors of hospitals with sustained superior performance on TPS, that is, "sustainers." PRINCIPAL FINDINGS: Only 8.4% of hospitals were classified as sustainers. Hospitals located in rural markets with a high Medicare Advantage penetration had a higher likelihood of being classified as sustainers. High RN staffing levels, lower Medicare share of inpatient days, not-for-profit ownership, and small size were all significant organizational predictors of sustained superior performance. CONCLUSIONS: Both modifiable characteristics, such as nurse staffing levels, and nonmodifiable characteristics, such as rural markets and small hospital size, are associated with the likelihood of hospitals sustaining superior performance over time. PRACTICE IMPLICATIONS: Managers need to carefully examine their staffing levels as they pursue interventions to sustain high TPS overtime. Moreover, factors such as Medicare share of inpatient days and size need to be considered when understanding barriers to sustained performance on Value-Based Purchasing domains.

Sustained Hospital Performance on Hospital Consumer Assessment of Healthcare Providers and Systems Survey Measures: What Are the Determinants?

EXECUTIVE SUMMARY: This study examines hospital characteristics associated with sustained superior performance on Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) measures. We classified hospitals as sustainers if they remained in the top 25th percentile of overall patient ratings of inpatient experience from 2009 through 2013. We classified hospital characteristics as modifiable or unmodifiable. Modifiable characteristics are operational measures that hospitals can change to improve performance; these characteristics include registered nurse (RN) staffing levels, presence of hospitalists, and level of physician integration. Unmodifiable characteristics are core structural dimensions, such as hospital size and teaching status, that require substantial investment to change, as well as market-level factors such as competition and unemployment rates. Using logistic regression analysis, we found that RN staffing levels, Medicare share of inpatient days, teaching status, and market competition were significant predictors of the likelihood that a given hospital sustained high levels of patient ratings over time (i.e., the likelihood of a hospital being classified as a sustainer). Hospitals with a higher ratio of inpatient days to RN staffing and higher Medicare share of inpatient days had lower odds of being classified as sustainers.

The Effects of Hospital-Level Factors on Patients' Ratings of Physician Communication.

The quality of physician-patient communication influences patient health outcomes and satisfaction with healthcare delivery. Yet, little is known about contextual factors that influence physicians' communication with their patients. The main purpose of this article is to examine organizational-level factors that influence patient perceptions of physician communication in inpatient settings. We used the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey and American Hospital Association data to determine patients' ratings of physician communication at the hospital level, and to collect information about hospital-level factors that can potentially influence physician communication. Our sample consisted of 2,756 hospitals. We ran a regression analysis to determine the predictors of poor physician communication, measured as the percentage of patients in a hospital who reported that physicians sometimes or never communicated well. In our sample of hospitals, this percentage ranged between 0% and 21%, with 25% of hospitals receiving poor ratings from more than 6% of patients. Three organizational factors had statistically significant negative associations with physician communication: for-profit ownership, hospital size, and hospitalists providing care in the hospital, On the other hand, the number of full-time-equivalent physicians and dentists per 10,000 inpatient days, physician ownership of the hospital, Medicare share of inpatient days, and public ownership were positively associated with patients' ratings of physician communication. Physician staffing levels are an understudied area in healthcare research. Our findings indicate that physician staffing levels affect the quality of physician communication with patients. Moreover, for-profit and larger hospitals should invest more in physician communication given the role that HCAHPS plays in value-based purchasing.

Efficiency and hospital effectiveness in improving Hospital Consumer Assessment of Healthcare Providers and Systems ratings.

BACKGROUND: Efficiency has emerged as a central goal to the operations of health care organizations. There are two competing perspectives on the relationship between efficiency and organizational performance. Some argue that organizational slack is a waste and that efficiency contributes to organizational performance, whereas others maintain that slack acts as a buffer, allowing organizations to adapt to environmental demands and contributing to organizational performance. PURPOSES: As value-based purchasing becomes more prevalent, health care organizations are incented to become more efficient and, at the same time, improve their patients' experiences and outcomes. Unused slack resources might facilitate the timely implementation of these improvements. Building on previous research on organizational slack and inertia, we test whether efficiency and other organizational factors predict organizational effectiveness in improving Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings. METHODOLOGY: We rely on data from the American Hospital Association and HCAHPS. We estimate hospital cost-efficiency by Stochastic Frontier Analysis and use regression analysis to determine whether efficiency, competition, hospital size, and other organizational factors are significant predictors of hospital effectiveness. FINDINGS: Our findings indicate that efficiency and hospital size have a significant negative association with organizational ability to improve HCAHPS ratings. PRACTICE IMPLICATIONS: Although achieving organizational efficiency is necessary for health care organizations, given the changes that are currently occurring in the U.S. health care system, it is important for health care managers to maintain a certain level of slack to respond to environmental demands and have the resources needed to improve their performance.

The effects of nurse staffing on hospital financial performance: competitive versus less competitive markets.

BACKGROUND: Hospitals facing financial uncertainty have sought to reduce nurse staffing as a way to increase profitability. However, nurse staffing has been found to be important in terms of quality of patient care and nursing-related outcomes. Nurse staffing can provide a competitive advantage to hospitals and as a result of better financial performance, particularly in more competitive markets. PURPOSE: In this study, we build on the Resource-Based View of the Firm to determine the effect of nurse staffing on total profit margin in more competitive and less competitive hospital markets in Florida. METHODOLOGY/APPROACH: By combining a Florida statewide nursing survey with the American Hospital Association Annual Survey and the Area Resource File, three separate multivariate linear regression models were conducted to determine the effect of nurse staffing on financial performance while accounting for market competitiveness. The analysis was limited to acute care hospitals. FINDINGS: Nurse staffing levels had a positive association with financial performance (ß = 3.3, p = .02) in competitive hospital markets, but no significant association was found in less competitive hospital markets. PRACTICE IMPLICATIONS: Hospitals in more competitive hospital markets should reconsider reducing nursing staff, as these cost-cutting measures may be inefficient and negatively affect financial performance.

Ambulatory surgery center and general hospital competition: entry decisions and strategic choices.

BACKGROUND: General hospitals are consistently under pressure to control cost and improve quality. In addition to mounting payers' demands, hospitals operate under evolving market conditions that might threaten their survival. While hospitals traditionally were concerned mainly with competition from other hospitals, today's reimbursement schemes and entrepreneurial activities encouraged the proliferation of outpatient facilities such as ambulatory surgery centers (ASCs) that can jeopardize hospitals' survival. PURPOSE: The purpose of this article was to examine the relationship between ASCs and general hospitals. More specifically, we apply the niche overlap theory to study the impact that competition between ASCs and general hospitals has on the survival chances of both of these organizational populations. METHODOLOGY: Our analysis examined interpopulation competition in models of organizational mortality and market demand. We utilized Cox proportional hazard models to evaluate the impact of competition from each on ASC and hospital exit while controlling for market factors. We relied on two data sets collected and developed by Florida's Agency for Health Care Administration: outpatient facility licensure data and inpatient and outpatient surgical procedure data. FINDINGS: Although ASCs do tend to exit markets in which there are high levels of ASC competition, we found no evidence to suggest that ASC exit rates are affected by hospital density. On the other hand, hospitals not only tend to exit markets with high levels of hospital competition but also experience high exit rates in markets with high ASC density. PRACTICE IMPLICATIONS: The implications from our study differ for ASCs and hospitals. When making decisions about market entry, ASCs should choose their markets according to the following: demand for outpatient surgery, number of physicians who would practice in the surgery center, and the number of surgery centers that already exist in the market. Hospitals, on the other hand, should account for competition from ASCs while making market-entry decisions and while developing their strategic plans.

The interaction between high-level electronic medical record adoption and hospitalist staffing levels: A focus on value-based purchasing.

OBJECTIVE: This study sought to understand the relationship of hospital performance with high-level electronic medical record (EMR) adoption, hospitalists staffing levels, and their potential interaction. MATERIALS AND METHODS: We evaluated 2,699 non-federal, general acute hospitals using 2016 data merged from four data sources. We performed ordinal logistic regression of hospitals' total performance score (TPS) on their EMR capability and hospitalists staffing level while controlling for other market- and individual-level characteristics. RESULTS: Hospitalists staffing level is shown to be positively correlated with TPS. High-level EMR adoption is associated with both short-term and long-term improvement on TPS. Large, urban, non-federal government hospitals, and academic medical centers tend to have lower TPS compared to their respective counterparts. Hospitals belonging to medium- or large-sized healthcare systems have lower TPS. Higher registered nurse (RN) staffing level is associated with higher TPS, while higher percentage of Medicare or Medicaid share of inpatient days is associated with lower TPS. DISCUSSION: Although the main effects of hospitalists staffing level and EMR capability are significant, their interaction is not, suggesting that hospitalists and EMR act through separate mechanisms to help hospitals achieve better performance. When hospitals are not able to invest on both simultaneously, given financial constraints, they can still reap the full benefits from each. CONCLUSION: Hospitalists staffing level and EMR capability are both positively correlated with hospitals' TPS, and they act independently to bolster hospital performance.

Is there an association between hospital staffing levels and inpatient-COVID-19 mortality rates?

OBJECTIVE: This study aims to investigate the relationship between RNs and hospital-based medical specialties staffing levels with inpatient COVID-19 mortality rates. METHODS: We relied on data from AHA Annual Survey Database, Area Health Resource File, and UnitedHealth Group Clinical Discovery Database. In phase 1 of the analysis, we estimated the risk-standardized event rates (RSERs) based on 95,915 patients in the UnitedHealth Group Database 1,398 hospitals. We then used beta regression to analyze the association between hospital- and county- level factors with risk-standardized inpatient COVID-19 mortality rates from March 1, 2020, through December 31, 2020. RESULTS: Higher staffing levels of RNs and emergency medicine physicians were associated with lower COVID-19 mortality rates. Moreover, larger teaching hospitals located in urban settings had higher COVID-19 mortality rates. Finally, counties with greater social vulnerability, specifically in terms of housing type and transportation, and those with high infection rates had the worst patient mortality rates. CONCLUSION: Higher staffing levels are associated with lower inpatient mortality rates for COVID-19 patients. More research is needed to determine appropriate staffing levels and how staffing levels interact with other factors such as teams, leadership, and culture to impact patient care during pandemics.

Specialty hospital market proliferation: Strategic implications for general hospitals.

BACKGROUND: Since the early 1990s, specialty hospitals have been continuously increasing in number. A moratorium was passed in 2003 that prohibited physicians' referrals of Medicare patients to newly established specialty hospitals if the physician has ownership stakes in the hospital. Although this moratorium expired in effect in 2007, many are still demanding that the government pass new policies to discourage the proliferation of specialty hospitals. PURPOSE: This study aimed at examining the regulatory and environmental forces that influence specialty hospitals founding rate. Specifically, we use the resource partitioning theory to investigate the relationship between general hospitals closure rates and the market entry of specialty hospitals. This study will help managers of general hospitals in their strategic thinking and planning. METHODOLOGY: We rely on secondary data resources, which include the American Hospital Association, Area Resource file, census, and Center for Medicare and Medicaid Services data, to perform a longitudinal analysis of the founding rate of specialty hospital in the 48 states. Specifically, we use the negative binomial generalized estimating equation approach available through Stata 9.0 to study the effect of general hospitals closure rate and environmental variables on the proliferation of specialty hospitals. FINDINGS: Specialty hospitals founding rate seems to be significantly related to general hospitals closure rates. Moreover, results indicate that economic, supply, regulatory, and financial conditions determine the founding rate of specialty hospitals in different states. PRACTICE IMPLICATIONS: The results from this study indicate that the closure of general hospitals creates market conditions that encourage the market entry of specialized health care delivery forms such as specialty hospitals. Managers of surviving general hospitals have to view the closure of other general hospitals not just as an opportunity to increase market share but also as a threat of competition from new forms of health care organizations.

Hospitalists staffing levels and hospital performance.

OBJECTIVE (OR STUDY QUESTION): To examine the association between hospitalists staffing levels and contract type with CMS Total Performance Score (TPS). DATA SOURCES/STUDY SETTING: Total performance scores were obtained from CMS, hospital-level data from the 2015 American Hospital Association Annual Survey Database, and unemployment rates from the Area Resource Health File. STUDY DESIGN: We used cluster analysis to classify hospitals based on the distribution of various hospitalist contracts, and we used regression analysis to examine the association between TPS and hospitalist staffing levels and contract distributions. Hospital-level predictors included hospitalists staffing levels, RN staffing levels, and Magnet status. Market-level variables were unemployment rates and competition. PRINCIPAL FINDINGS: Higher staffing levels of employed hospitalists or hospitalists with a group contract are associated with higher TPS (with coefficient estimates of 0.85 and 0.83, respectively, and the same standard error of 0.22). Higher staffing levels of hospitalists under individual contract are negatively associated with TPS (with coefficient estimate of -0.43 and standard error of 0.21). Based on the regression analysis using hospital clusters as independent variables, hospitals with individual contracts or without hospitalists providing care had significantly worse TPS compared to hospitals that predominantly employ hospitalists (with coefficient estimate of -1.80 and standard error of 0.61). Magnet status, RN staffing levels, and small and medium size were positively associated with TPS. Medicare share of inpatient days, teaching status, AMCs, and for-profit and public nonfederal ownership were negatively associated with TPS. CONCLUSIONS: Adequate hospitalist staffing level is important for hospitals to achieve better performance. Hospitals need to consider the mix of arrangements or contracts that they have with hospitalists.

Efficiency and profitability in US not-for-profit hospitals.

This article examines the relationship between hospital profitability and efficiency. A cross-section of 1317 U.S. metropolitan, acute care, not-for-profit hospitals for the year 2015 was employed. We use a frontier method, stochastic frontier analysis, to estimate hospital efficiency. Total margin and operating margin were used as profit variables in OLS regressions that were corrected for heteroskedacity. In addition to estimated efficiency, control variables for internal and external correlates of profitability were included in the regression models. We found that more efficient hospitals were also more profitable. The results show a positive relationship between profitability and size, concentration of output, occupancy rate and membership in a multi-hospital system. An inverse relationship was found between profits and academic medical centers, average length of stay, location in a Medicaid expansion state, Medicaid and Medicare share of admissions, and unemployment rate. The results of a Hausman test indicates that efficiency is exogenous in the profit equations. The findings suggest that not-for-profit hospitals will be responsive to incentives for increasing efficiency and use market power to increase surplus to pursue their objectives.

A robust analysis of hospital efficiency and factors affecting variability.

The objectives of this paper are to use data envelopment analysis to measure hospital inefficiency in a way that accounts for patient outcomes and to study the association between organizational factors, such as hospital-physicians integration level and teaching status, and market competition with hospital inefficiency. We apply the robust data envelopment analysis approach to a sample of private (both not-for-profit and for-profit) hospitals operating in the United States. Our data envelopment analysis model includes mortality and readmission rates as bad outputs and admissions, surgeries, emergency room, and other visits as good outputs. Therefore, our measurement of hospital inefficiency accounts for quality. We then use a subsampling regression analysis to determine the predictors of hospital inefficiency. For-profit, fully integrated and teaching hospitals were more efficient than their counterparts. Also hospitals located in more competitive markets were more efficient than those located in less competitive markets. Incorporating quality in the measurement of hospital efficiency is key for producing valid efficiency scores. Hospitals in less competitive markets need to improve their efficiency levels. Moreover, high levels of hospital physician integration might be instrumental in ensuring that hospitals achieve their efficiency goals.

Hospital characteristics and 30-day all-cause readmission rates.

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) publicly reports hospital-wide all-cause readmission rates, which are key indicators of quality and waste. Understanding hospital characteristics that are associated with lower readmission rates is important. OBJECTIVES: The main objective of this article is to identify hospital characteristics associated with lower readmission rates. Specifically, we focus on the relationship between hospitalist staffing levels, the level of physician integration, and physician ownership with hospital-wide all-cause readmissions. METHODS: We rely on data from CMS, American Hospital Association Annual Survey Database, and Area Health Resource File. We use ordinary least square regression to assess the association between readmission rates and hospitalist staffing levels, physician integration, physician ownership, and the presence of a medical home model, while controlling for key organizational and market factors such as registered nurse (RN) staffing levels and competition. RESULTS: Higher hospitalist staffing levels, the fully integrated physician model, and physician ownership were associated with lower readmission rates. The addition of 1 hospitalist per general and surgical bed was associated with a 0.77 percentage-points decrease in adjusted 30-day all-cause readmission rates. Fully integrated hospitals had adjusted 30-day all-cause readmission rates 0.09 percentage points lower than non-fully integrated hospitals, and hospitals partially or fully owned by physicians had adjusted readmission rates 0.36 percentage points lower than non-physician-owned hospitals. CONCLUSIONS: Hospitals should focus on modifiable organizational factors that influence patient outcomes such as hospitalist and RN staffing levels and explore hospital-physician arrangements that result in the greatest alignment between hospital and physician incentives. Journal of Hospital Medicine 2016;11:682-687. © 2016 Society of Hospital Medicine.

Predictors of language service availability in U.S. hospitals.

BACKGROUND: Hispanics comprise 17% of the total U.S. population, surpassing African-Americans as the largest minority group. Linguistically, almost 60 million people speak a language other than English. This language diversity can create barriers and additional burden and risk when seeking health services. Patients with Limited English Proficiency (LEP) for example, have been shown to experience a disproportionate risk of poor health outcomes, making the provision of Language Services (LS) in healthcare facilities critical. Research on the determinants of LS adoption has focused more on overall cultural competence and internal managerial decision-making than on measuring LS adoption as a process outcome influenced by contextual or external factors. The current investigation examines the relationship between state policy, service area factors, and hospital characteristics on hospital LS adoption. METHODS: We employ a cross-sectional analysis of survey data from a national sample of hospitals in the American Hospital Association (AHA) database for 2011 (N= 4876) to analyze hospital characteristics and outcomes, augmented with additional population data from the American Community Survey (ACS) to estimate language diversity in the hospital service area. Additional data from the National Health Law Program (NHeLP) facilitated the state level Medicaid reimbursement factor. RESULTS: Only 64% of hospitals offered LS. Hospitals that adopted LS were more likely to be not-for-profit, in areas with higher than average language diversity, larger, and urban. Hospitals in above average language diverse counties had more than 2-fold greater odds of adopting LS than less language diverse areas [Adjusted Odds Ratio (AOR): 2.26, P< 0.01]. Further, hospitals with a strategic orientation toward diversity had nearly 2-fold greater odds of adopting LS (AOR: 1.90, P< 0.001). CONCLUSION: Our findings support the importance of structural and contextual factors as they relate to healthcare delivery. Healthcare organizations must address the needs of the population they serve and align their efforts internally. Current financial incentives do not appear to influence adoption of LS, nor do Medicaid reimbursement funds, thus suggesting that further alignment of incentives. Organizational and system level factors have a place in disparities research and warrant further analysis; additional spatial methods could enhance our understanding of population factors critical to system-level health services research.

Dynamics of ambulatory surgery centers and hospitals market entry.

In this article, we investigate the diversity of healthcare delivery organizations by comparing the market determinants of hospitals entry rates with those of ambulatory surgery centers (ASCs). Unlike hospitals, ASCs is one of the growing populations of specialized healthcare delivery organizations. There are reasons to believe that firm entry patterns differ within growing organizational populations since these markets are characterized by different levels of organizational legitimacy, technological uncertainty, and information asymmetry. We compare the entry patterns of firms in a mature population of hospitals to those of firms within a growing population of ASCs. By using patient-level datasets from the state of Florida, we break down our explanatory variables by facility type (ASC vs. hospital) and utilize negative binomial regression models to evaluate the impact of niche density on ASC and hospital entry. Our results indicate that ASCs entry rates is higher in markets with overlapping ASCs while hospitals entry rates are less in markets with overlapping hospitals and ASCs. These results are consistent with the notion that firms in growing populations tend to seek out crowded markets as they compete to occupy the most desirable market segments while firms in mature populations such as general hospitals avoid direct competition.

Hospital-physician relationships: implications from the professional service firms literature.

PURPOSE: The hospital-physician relationship (HPR) has been the focus of many scholars given the potential impact of this relationship on hospitals' ability to achieve socially and organizationally desirable health care outcomes. Hospitals are dominated by professionals and share many commonalities with professional service firms (PSFs). In this chapter, we explore an alternative HPR based on the governance models prevalent in PSFs. DESIGN/METHODOLOGY APPROACH: We summarize the issues presented by current HPRs and discuss the governance models dominant in PSFs. FINDINGS: We identify the non-equity partnership model as a governance archetype for hospitals; this model accounts for both the professional dominance in health care decisions and the increasing demand for higher accountability and efficiency. RESEARCH LIMITATIONS: There should be careful consideration of existing regulations such as the Stark law and the antikickback statue before the proposed governance model and the compensation structure for physician partners is adopted. RESEARCH IMPLICATIONS: While our governance archetype is based on a review of the literature on HPRs and PSFs, further research is needed to test our model. PRACTICAL IMPLICATIONS: Given the dominance of not-for-profit (NFP) ownership in the hospital industry, we believe the non-equity partnership model can help align physician incentives with those of the hospital, and strengthen HPRs to meet the demands of the changing health care environment. ORIGINALITY/VALUE: This is the first chapter to explore an alternative hospital-physician integration strategy by examining the governance models in PSFs, which similar to hospitals have a high reliance on a predominantly professional staff.